Chil ild Care and Maternal Employment: Evidence fr from Vie ietnam Hai-Anh Dang, Masako Hiraga, and Cuong Viet Nguyen (DECDG & Mekong Development Research Institute) ******************** UNE Business School Seminar Armidale November 2019
I. Introduction (1) - Women earn less income, less likely to participate in the labor market, esp. in low- and middle-income countries (World Bank, 2012) - We examine impacts of pre-school (age 1- 5) child care on women’s labor market outcomes in Vietnam • strong effect on women’s LMP • increase probability of working in a formal wage-earning job • increase women’s total annual wages, household income per capita and reduce poverty • effect of child care is larger for younger children, and younger and highly-educated mothers - We address endogeneity issue with threshold in the birth months of children • children’s enrollment in kindergartens or primary schools based on current age instead of completed age • use RDD method to compare children born in December vs. January in two adjacent years
I. Introduction (2) - Our contributions • add to the thin literature on women’s labor outcomes in developing countries larger sample nationally representative data • esp., mixed results on impacts of childcare for both richer and poorer countries positive impacts in Argentina (Berlinksi et al, 2011), but zero effects for urban Chinese mothers (Li, 2017) elasticity of maternal employment to child-care costs differs due to differences in samples of women and children, estimation methods, and country contexts (Blau & Currie, 2006; Akgunduz & Plantega, 2018) • study rich employment outcomes (quality aspects) self-employed, employed, farm and non-farm, skilled employment, and wage work household-level outcomes, incl., income, poverty, household size, migration, and co-residence with grandparents in the short term and the medium term • Vietnam is an interesting case study despite solid growth, half (44%) self-employed in agriculture, and more than two-thirds (68%) of workers self-employed lower proportion of women working in a wage job (30%) than men (42%) half (53%) of children age 1-5 do not attend child care
II. Data - Vietnam Household Living Standard Surveys (VHLSS) from 2010 to 2016 - used full sample of the VHLSS to increase the number of children born in January and February - Sample size i. VHLSS 2010: 46,995 households with 185,696 household members. ii. VHLSS 2012: 46,996 households with 182,042 household members. iii. VHLSS 2014: 46,335 households with 178,267 household members. iv. VHLSS 2016: 46,380 households with 175,340 household members.
III. Child care system Figure 1: Percentage of children attending child care centers - Some main features 79.6 80 • In 2016, 44% of urban children aged 68.9 below 6 attended child care centers and 65.6 kindergartens, for rural children 35%. 60 50.9 47.7 40 32.2 19.8 20 14.6 3.4 3 .2 .4 0 Age 0 Age 1 Age 2 Age 3 Age 4 Age 5 2010 2016
IV. Estimation method (1) - Regression Discontinuity Design (RDD) Figure 2: Proportion of enrolled school-age children and month of birth 𝐸 𝑗,𝑘 = 𝛽 + 𝛾𝐸𝑓𝑑𝑓𝑛𝑐𝑓𝑠 𝑗,𝑘 + 𝛿𝑌 𝑗,𝑘 + 𝜗 𝑗,𝑘 (2) .55 𝑍 𝑗,𝑘 = 𝜀 + 𝜄𝐸 𝑗,𝑘 + 𝜌𝑌 𝑗,𝑘 + 𝑣 𝑗,𝑘 (3) .5 - One- month bandwidth for children’s born in December and January .45 .4 .35 Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Month of birth Sample average within bin Polynomial fit of order 2
IV. Estimation results (1) Figure 5. Dis. of children by month of birth Table 2. First-stage probit regression (marginal effects) Dependent variable is child care attendance 12 Explanatory variables Pooled sample Children aged 1-3 Children aged 3-5 10 0.092*** 0.080*** 0.097*** Instrument (child born in December) (0.017) (0.018) (0.024) 0.046*** 0.033** 0.048*** Age 8 (0.013) (0.014) (0.017) -0.639*** -0.548** -0.697*** Age squared (0.189) (0.213) (0.249) 6 Ethnic minority 0.021 -0.029 0.049 (0.022) (0.021) (0.032) 4 0.016*** 0.012*** 0.022*** Number of years of schooling (0.002) (0.002) (0.003) 2 Dummy year 2010 Reference Dummy year 2012 0.025 -0.033 0.013 0 (0.021) (0.021) (0.032) Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 0.039* 0.015 0.089*** Dummy year 2014 Month of birth (0.022) (0.024) (0.033) Dummy year 2016 0.078*** 0.025 0.088*** Proportion 95% confidence interval (0.023) (0.024) (0.032) Observations 3,863 1,718 2,145 Pseudo R2 0.029 0.072 0.038 This table reports the marginal effects from the logit regression of child care attendance on the instrumental variable and control variables of mothers. The observations in these regressions are mothers of children aged 1-6. Further check on the instrument Heteroskedasticity-robust standard errors in parentheses. Standard errors are corrected for sampling weights and cluster correlation at the commune level. *** p<0.01, ** p<0.05, * p<0.1. Source: Estimation from VHLSS 2010, 2012, 2014 and 2016.
IV. Estimation results (2) Table 3: The effect of child care attendance on mothers’ employment Dependent variables Panel A. Short-term effects Panel B. Medium-term effects All children Children Children All children Children Children aged 1-3 aged 3-5 aged 1-3 aged 3-5 Bivariate probit model (marginal effects) Working -0.110 -0.170 -0.128 -0.016 0.037 0.146 (0.126) (0.144) (0.090) (0.110) (0.060) (0.124) In wage-paying job 0.411*** 0.490*** 0.408*** 0.377*** 0.477*** 0.333*** (0.010) (0.033) (0.021) (0.024) (0.038) (0.087) In self-employed -0.103 -0.240** 0.070 0.043 -0.004 0.089 nonfarm work (0.105) (0.092) (0.149) (0.108) (0.150) (0.145) In self-employed farm -0.454*** -0.563*** -0.440*** -0.419*** -0.384*** -0.297*** work (0.011) (0.053) (0.008) (0.032) (0.078) (0.103) In skilled work 0.108 -0.146 0.043 -0.055 0.187 -0.239 (0.835) (1.260) (0.238) (0.384) (0.143) (0.157) In a formal job 0.257*** 0.172 0.264*** 0.149 0.382 0.017 (0.035) (0.229) (0.077) (0.206) (0.349) (0.296) 2SLS Log of monthly working 0.155 0.378 -0.009 0.293 0.489 0.206 hours (0.209) (0.358) (0.255) (0.312) (0.470) (0.463) Log of hourly wage 0.572 0.948 0.141 -0.275 -0.104 -0.421 (0.460) (0.649) (0.568) (0.478) (0.511) (0.842) Log of wage for the last 0.525 0.951 0.113 -0.078 0.071 -0.286 month (0.410) (0.586) (0.521) (0.523) (0.580) (0.895) Log of total wage for the 0.903* 1.165 0.645 -0.068 0.397 -0.527 past 12 months (0.524) (0.743) (0.666) (0.678) (0.733) (1.183)
IV. Estimation results (3) - Robustness checks • 2SLS and control functions (Rivers and Vuong, 1988; Woolridge, 2015) • vary bandwidths to 2 or 3 months • falsification analysis
IV. Estimation results (4) Table 5. 2SLS regression of household-level outcomes on child care attendance Log of Household is Living with Mothers are Household Explanatory variables income per poor grandparents migrating size capita Child care attendance 0.428* -0.222* 0.009 0.029 0.047 (0.237) (0.124) (0.053) (0.050) (0.363) Ethnic minority -0.970*** 0.547*** 0.021*** -0.017*** 0.527*** (0.030) (0.018) (0.008) (0.005) (0.058) Dummy year 2010 Reference Dummy year 2012 0.328*** -0.011 0.039*** -0.008 0.112** (0.034) (0.019) (0.006) (0.006) (0.050) Dummy year 2014 0.530*** -0.070*** 0.034*** -0.007 0.094* (0.039) (0.021) (0.007) (0.007) (0.057) Dummy year 2016 0.678*** -0.106*** 0.041*** 0.005 0.127** (0.041) (0.021) (0.009) (0.009) (0.061) Constant 9.316*** 0.323*** -0.008 0.014 4.193*** (0.101) (0.053) (0.022) (0.021) (0.153) Observations 3,863 3,863 3,863 3,863 3,863
IV. Estimation results (5) Table 6. Probability of having a wage job with interactions between child schooling and demographic variables of children and mothers (probit models) Interaction variables Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Child care attendance * age -0.003 (-0.330) 0.010** Child care attendance * schooling years (2.222) -0.071* Child care attendance * ethnic minority (-1.744) 0.004* Child care attendance * boy (1.794) -0.038 Child care attendance * birth order (-1.439) Child care attendance * -0.063 Lagged grandparents in (-1.028) household Observations 3,863 3,863 3,863 3,863 3,863 3,863 Pseudo R2 0.103 0.104 0.103 0.103 0.106 0.106
IV. Estimation results (6) Table 7. Probability of having a wage job with interactions between child schooling and demographic variables of children and commune variables Interaction variables Model 1 Model 2 Model 3 Model 4 Model 5 -0.104 Child care attendance * Public child care center (-1.415) -0.006*** Child care attendance * distance to nearest town (-2.795) -0.035 Child care attendance * village accessible by car (-0.782) -0.028 Child care attendance * kindergarten in village (-0.678) 0.063* Child care attendance * log of district per capita income (1.801) Observations 3,863 2,853 2,853 2,853 3,863 R-squared 0.105 0.071 0.065 0.067 0.123
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